An In-Depth Survey of Underwater Image Enhancement and Restoration

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Miao YANG
  • Jintong HU
  • Chongyi LI
  • Gustavo ROHDE
  • Yixiang DU
  • And 1 others
  • Ke HU

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)123638-123657
Journal / PublicationIEEE Access
Volume7
Online published2 Aug 2019
Publication statusPublished - 2019

Link(s)

Abstract

Images taken under water usually suffer from the problems of quality degradation, such as low contrast, blurring details, color deviations, non-uniform illumination, etc. As an important problem in image processing and computer vision, the restoration and enhancement of underwater image are necessary for numerous practical applications. Over the last few decades, underwater image restoration and enhancement have been attracting an increasing amount of research effort. However, a comprehensive and in-depth survey of related achievements and improvements is still missing, especially the survey of underwater image dataset which is a key issue in underwater image processing and intelligent application. In this exposition, we first summarize more than 120 studies about the latest progress in underwater image restoration and enhancement, including the techniques, datasets, available codes, and evaluation metrics. We analyze the contributions and limitations of existing methods to facilitate the comprehensive understanding of underwater image restoration and enhancement. Furthermore, we provide detailed objective evaluations and analysis of the representative methods on five types of underwater scenarios, which verifies the applicability of these methods in different underwater conditions. Finally, we discuss the potential challenges and open issues of underwater image restoration and enhancement and suggest possible research directions in the future.

Research Area(s)

  • Underwater image quality degradation, underwater image database, underwater image enhancement and restoration, underwater image quality evaluation, COLOR CORRECTION, HAZE REMOVAL, TRANSMISSION, VISIBILITY, ALGORITHM, MODEL

Citation Format(s)

An In-Depth Survey of Underwater Image Enhancement and Restoration. / YANG, Miao; HU, Jintong; LI, Chongyi; ROHDE, Gustavo; DU, Yixiang; HU, Ke.

In: IEEE Access, Vol. 7, 2019, p. 123638-123657.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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